May 17, 2020

Have seamless digital customer experiences become mission critical?

Harry Menear
5 min
Gigabit Magazine explores the strategies being adopted by companies that want not simply to survive this age of seamless consumer experience, but to thrive in it. 
Across every industry in every market, one thing has become clear in 2019: this is the year of the customer.

Ubiquitous advertising, economic discomfo...

Across every industry in every market, one thing has become clear in 2019: this is the year of the customer.

Ubiquitous advertising, economic discomfort in a shrinking middle class, more ways than ever for people to self-determine the companies they deal with, a hunger for on-demand and personalised products and services, and a younger consumer class grown increasingly distrustful of an unfair capitalist system, are all conspiring to firmly put the ball back in the court of corporations when it comes to attracting and retaining a customer base. 

Back in 2018, James Paine, the Founder of West Realty Advisors wrote, in a piece for Inc, that “twenty years ago, if you paid for a product or service and you weren't happy with what you received, the best you could hope for was that if you sent in a letter of complaint, you'd eventually receive a refund. You could tell a couple of friends and maybe they'd tell their friends, but that was about it. Nowadays, though, if a customer has a bad experience then they can post about it online, and if they post about it online then it can go viral and even seriously damage the overall value of your brand. After all, all it took was one tweet from Kylie Jenner to knock US$1.3bn off Snapchat's valuation.” 

The message from consumers is clear: “treat us right or perish.” 

This month, Gigabit Magazine explores the strategies being adopted by companies that want not simply to survive this age of seamless consumer experience, but to thrive in it. 

Victoria Holt, CEO of digital manufacturer Protolabs, agrees that customer expectations in her industry have changed over the past decade. “People expect improvements at a pretty fast clip these days. So, being able to very quickly design, prototype and launch products is a critical success factor for manufacturers today,” she explains, adding that “there's more mass-customisation too, which is another thing that not only requires rapid innovation, but the capacity to produce products in lower quantities as you customise them for specific end uses. Again, this lends itself to a more digitalised manufacturing process.”

This emphasis on harnessing the power of digital transformation is part and parcel with the ouroboric relationship between the company and customer. Companies digitally transform to offer products that are more personalised and readily available, and in return, this drives customer expectations and the standards are becoming more exacting every year as the customers take more and more control. 

“For the last 50 years, software development has been specification-centric. Teams created software that complied with a specification. That just doesn’t work anymore,” says Antony Edwards, Chief Operating Officer of artificial intelligence, analytics and software solutions company, Eggplant. “Software teams need to use customer analytics to become user-centric and create software that delights users and drives business outcomes.”

Edwards’ observations are backed by a recent white paper from Adobe. Noting that the most successful modern companies are the ones that have digitally transformed themselves, Adobe warns that “transformation needs to be driven with a purpose. For top businesses, that purpose is customer experience.” Companies that place customer experience at the top of their list of priorities are more successful than those who adopt a ‘push’ mentality. 


But what do those customers want? High level concepts like “customisability” and “on-demand” are a good start, but to better understand the specific things consumers want from them, successful companies are doubling down on analytics and diverting more and more resources, both to understanding their consumers and to providing a seamless experience. “Fast food stores are employing user analytics to understand how their staff are using point-of-sale terminals and then using this information to update the point-of-sale terminal so that customers are served faster,” says Edwards. “Retailers are using a combination of user and technical analytics to understand how technical factors such as website speed and design factors such as high-resolution graphics, impact purchases. They then feed this automatically back into their software development to optimize revenue.”

Across the board, industry leaders are moving as one towards a more informed company-customer relationship. In Gartner’s recent Customer Experience Trends Survey, it was revealed that, in 2018, two-thirds of companies increased their customer experience technology investments, with 52% reporting that they intended to increase spending further in 2019. In last year’s survey, Gartner found that 81% of companies expect customer experience to be the most important competition metric by 2020. 

Seeking to perfect the customer experience is going to become an even greater point of differentiation for companies in the next few years. Social media is a valuable tool for companies to understand, sell to and interact with their customer bases, but the sword swings both ways. Debacles like Fyre Festival and Kylie Jenner’s Snapchat Tweet prove that brands have nowhere to hide anymore; the customer experience must be seamless, curated and on-demand. Companies that want to succeed in what may become the Decade of the Customer need expert help - a fact that means the global Customer Experience Analytics Market is expected to grow to around $12bn by 2023 - and to embrace the power of digital.

Vinod Muthukrishnan, co-founder and CEO of customer experience management software company CloudCherry, lives this reality every day. “Customer retention is lower than it ever has been. The millennial audience is actually much more conscious of business ethics, the environment and corporate social responsibility than the two generations before it, mine included,” he explains.

When asked about the key to a great customer experience, Muthukrishnan said: “We're going back to the basics. In many ways, the more digitisation we do, the more humanisation the customer demands. You can use machine learning, you can use bots - you do whatever, as long as it's aimed at actually giving that customer a more personal experience.” 

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Jun 11, 2021

Google AI Designs Next-Gen Chips In Under 6 Hours

3 min
Google AI’s deep reinforcement learning algorithms can optimise chip floor plans exponentially faster than their human counterparts

In a Google-Nature paper published on Wednesday, the company announced that AI will be able to design chips in less than six hours. Humans currently take months to design and layout the intricate chip wiring. Although the tech giant has been working in silence on the technology for years, this is the first time that AI-optimised chips have hit the mainstream—and that the company will sell the result as a commercial product. 


“Our method has been used in production to design the next generation of Google TPU (tensor processing unit chips)”, the paper’s authors, Azalea Mirhoseini and Anna Goldie wrote. The TPU v4 chips are the fastest Google system ever launched. “If you’re trying to train a large AI/ML system, and you’re using Google’s TensorFlow, this will be a big deal”, said Jack Gold, President and Principal Analyst at J.Gold Associates


Training the Algorithm 

In a process called reinforcement learning, Google engineers used a set of 10,000 chip floor plans to train the AI. Each example chip was assigned a score of sorts based on its efficiency and power usage, which the algorithm then used to distinguish between “good” and “bad” layouts. The more layouts it examines, the better it can generate versions of its own. 


Designing floor plans, or the optimal layouts for a chip’s sub-systems, takes intense human effort. Yet floorplanning is similar to an elaborate game. It has rules, patterns, and logic. In fact, just like chess or Go, it’s the ideal task for machine learning. Machines, after all, don’t follow the same constraints or in-built conditions that humans do; they follow logic, not preconception of what a chip should look like. And this has allowed AI to optimise the latest chips in a way we never could. 


As a result, AI-generated layouts look quite different to what a human would design. Instead of being neat and ordered, they look slightly more haphazard. Blurred photos of the carefully guarded chip designs show a slightly more chaotic wiring layout—but no one is questioning its efficiency. In fact, Google is starting to evaluate how it could use AI in architecture exploration and other cognitively intense tasks. 


Major Implications for the Semiconductor Sector 

Part of what’s impressive about Google’s breakthrough is that it could throw Moore’s Law, the axion that the number of transistors on a chip doubles every five years, out the window. The physical difficulty of squeezing more CPUs, GPUs, and memory on tiny silicon die will still exist, but AI optimisation may help speed up chip performance.


Any chance that AI can help speed up current chip production is welcome news. Though the U.S. Senate recently passed a US$52bn bill to supercharge domestic semiconductor supply chains, its largest tech firms remain far behind. According to Holger Mueller, principal analyst at Constellation Research, “the faster and cheaper AI will win in business and government, including with the military”. 


All in all, AI chip optimisation could allow Google to pull ahead of its competitors such as AWS and Microsoft. And if we can speed up workflows, design better chips, and use humans to solve more complex, fluid, wicked problems, that’s a win—for the tech world and for society. 



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